For Heads-of · Practitioner
Performance Metric
A quantitative measure of how well an AI model or system performs on a task, such as accuracy, precision, recall, F1 score, or domain-specific measures.
- performance metrics
- evaluation
- accuracy
- measurement
Common Metrics
Accuracy (fraction of correct predictions), precision (of positive predictions, how many are truly positive), recall (of actual positives, how many did we find), and F1 score (harmonic mean balancing precision and recall).
Limitation
A single metric rarely tells the full story. Models can be accurate overall while performing poorly on minority groups, creating discrimination despite good aggregate metrics.
Governance Requirement
Organizations must track disaggregated metrics by demographic group, domain, and use case. Fairness requires monitoring that the system performs acceptably across all relevant subgroups.